Advantages of Bayesian monitoring methods in deciding whether and when to stop a clinical trial: an example of a neonatal cooling trial.

Published online

Journal Article

BACKGROUND: Decisions to stop randomized trials are often based on traditional P value thresholds and are often unconvincing to clinicians. To familiarize clinical investigators with the application and advantages of Bayesian monitoring methods, we illustrate the steps of Bayesian interim analysis using a recent major trial that was stopped based on frequentist analysis of safety and futility. METHODS: We conducted Bayesian reanalysis of a factorial trial in newborn infants with hypoxic-ischemic encephalopathy that was designed to investigate whether outcomes would be improved by deeper (32 °C) or longer cooling (120 h), as compared with those achieved by standard whole body cooling (33.5 °C for 72 h). Using prior trial data, we developed neutral and enthusiastic prior probabilities for the effect on predischarge mortality, defined stopping guidelines for a clinically meaningful effect, and derived posterior probabilities for predischarge mortality. RESULTS: Bayesian relative risk estimates for predischarge mortality were closer to 1.0 than were frequentist estimates. Posterior probabilities suggested increased predischarge mortality (relative risk > 1.0) for the three intervention groups; two crossed the Bayesian futility threshold. CONCLUSIONS: Bayesian analysis incorporating previous trial results and different pre-existing opinions can help interpret accruing data and facilitate informed stopping decisions that are likely to be meaningful and convincing to clinicians, meta-analysts, and guideline developers. TRIAL REGISTRATION: ClinicalTrials.gov NCT01192776 . Registered on 31 August 2010.

Full Text

Duke Authors

Cited Authors

  • Pedroza, C; Tyson, JE; Das, A; Laptook, A; Bell, EF; Shankaran, S; Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network,

Published Date

  • July 22, 2016

Published In

Volume / Issue

  • 17 / 1

Start / End Page

  • 335 -

PubMed ID

  • 27450203

Pubmed Central ID

  • 27450203

Electronic International Standard Serial Number (EISSN)

  • 1745-6215

Digital Object Identifier (DOI)

  • 10.1186/s13063-016-1480-4

Language

  • eng

Conference Location

  • England